To bridge the gap between a small local model (like a 2B or 7B Gemma) and a
deterministic state machine, we must avoid nested data structures entirely.
Small models struggle with context-window degradation, often hallucinating
closing brackets in JSON, misaligning YAML indentation, or losing track of
deep topological graphs.
The most resilient format for this is a Flat AST (Abstract Syntax Tree)
translated into Line-Oriented Opcodes.
By reducing the Semantic Programming from Stage 1 into a linear sequence of
prefix-commands, you create a structure that a small LLM can generate
token-by-token with high accuracy. Meanwhile, your deterministic parser only
needs a simple lexer to read the first token of a line to know exactly which
execution state to enter, much like a custom bytecode execution engine.
Here is a blueprint for that Stage 2 minimalist format:
The "Flat Semantic Opcode" Format (FSO)
The rules for this format are strictly optimized for a state machine lexer:
 * Line-by-Line Execution: Every statement occupies exactly one line. No
multi-line strings (use 
).
 * Prefix Commands: The first word of every line is a strict, all-caps OPCODE.
 * Space-Delimited Arguments: Arguments follow the opcode, separated by
spaces. Strings are encapsulated in double quotes.
 * No Nesting: Conditional logic is flattened using LABELS and JUMPS,
mimicking assembly or basic LPC virtual machine mechanics.
The Core Instruction Set
| Opcode | Arguments | Action for the Deterministic Parser |
|---|---|---|
| VAR | [NAME] [TYPE] [VALUE] | Allocates memory. Types: STR, NUM, BOOL, ARR.
|
| LBL | [NAME] | Marks a position in the execution array for jumping. |
| JMP | [LABEL] | Unconditionally moves the execution pointer to a label. |
| JMP_IF | [CONDITION] [LABEL] | Evaluates a condition; if true, moves the
pointer. |
| SET | [NAME] [VALUE] | Mutates an existing variable in the state machine. |
| ADD | [ITEM] [TARGET_ARR] | Pushes an item into a specified array. |
| OUT | [STRING] | Emits a string to the user interface. |
| INP | [VAR_NAME] | Blocks execution, waits for user input, assigns to
variable. |
Translation Example
Let's look at how the LLM would translate the Stage 1 natural language into
the Stage 2 FSO.
Stage 1: Approved Human Specification
> IF CURRENT_ROOM IS "CELL":
> PRINT "You are in a sterile room."
> IF INVENTORY DOES NOT CONTAIN "WRENCH":
> PRINT "A rusted WRENCH lies under a cot."
> 
Stage 2: Machine Code (Gemma Output)
VAR CURRENT_ROOM STR "CELL"
VAR INVENTORY ARR []

LBL EVAL_CELL
IS_NOT CURRENT_ROOM "CELL" JMP EVAL_CORRIDOR
OUT "You are in a sterile room."

LBL CHECK_WRENCH
CONTAINS INVENTORY "WRENCH" JMP WAIT_COMMAND
OUT "A rusted WRENCH lies under a cot."

LBL EVAL_CORRIDOR
...

How the Bridge Works
 * The LLM as the "Linker": You prompt the small Gemma model with the Stage 1
text and the strict Opcode vocabulary. Its only job is to perform translation
and topological sorting, outputting the flat commands.
 * The Lexer/Parser: You write a fast, deterministic C or Node.js runtime. It
reads the LLM's output line-by-line, splitting the string.
 * The State Machine VM: tokens[0] (e.g., VAR) triggers a switch statement.
The runtime executes the logic, manages the memory handles for variables, and
yields when it hits an INP opcode.
Because the parser is completely rigid, if the local LLM hallucinates an
opcode (e.g., PRINT_TEXT instead of OUT), the parser instantly throws a
precise error (Unknown Opcode at Line X), which can be fed automatically back
to the LLM to correct itself without human intervention.
Do you think a linear, label-and-jump structure like this would map cleanly to
the compilation pipelines you are envisioning, or would you prefer a format
that preserves block structures (like IF / END_IF) for the parser to handle?